MétaCan
Menu
Back to cohort
Record W4417143494 · doi:10.1080/15438627.2025.2599859

Dental health status of professional football players during the Qatar 2023 AFC Asian Cup: a preliminary study

2025· article· en· W4417143494 on OpenAlexaff
Mohammed Alsaey, Dania Almasri, Montassar Tabben, Marco Cardinale, Abdulaziz Al-Kuwari, Gurcharan Singh, Atef Hashem

Bibliographic record

VenueResearch in Sports Medicine · 2025
Typearticle
Languageen
FieldHealth Professions
TopicDental Trauma and Treatments
Canadian institutionsConfederation College
FundersQatar National Library
KeywordsFootballFootball playersGingivitisPericoronitisOral healthAthletesPeriodontal diseaseDental health

Abstract

fetched live from OpenAlex

Oral health is increasingly recognized as an important factor influencing athletic performance and overall quality of life; however, limited data are available on elite football players in Asia. This cross-sectional clinical study evaluated the oral health status of professional players participating in the Asian Football Cup held in Qatar between January and February 2023. Three calibrated dentists conducted standardized clinical examinations on 70 randomly selected players (mean age: 26.8 years) using the DMFT, BPE, and BEWE indices to assess dental caries, periodontal health, erosive tooth wear, wisdom teeth status, trauma, and temporomandibular joint (TMJ) disorders. Dental caries was present in 85.7% of players (mean DED = 5.6), and 77.1% had restorations. Gingivitis affected 82.9%, while 12.9% showed signs of periodontitis. Tooth erosion was detected in 88.6%, with 10% classified as high risk. Partially erupted wisdom teeth were identified in 38.6%, pericoronitis in 7.1%, sports-related trauma in 30%, and TMJ disorders in 21.4%. These findings highlight a substantial oral disease burden and support integrating preventive dental care into routine athlete health programs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.139
GPT teacher head0.559
Teacher spread0.420 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueResearch in Sports MedicineSame topicDental Trauma and TreatmentsFrench-language works237,207